We are thrilled to announce the general availability of IBM StreamSets for real-time data integration.

To maintain an edge over competitors and improve their bottom-line without undermining growth, leaders need to steer organizations effectively, making decisions that are informed by current data, quickly. Indeed, highly data-driven organizations are three times more likely to report significant improvements in decision-making compared to those who rely less on data. 

But organizations face significant challenges in accessing reliable, up-to-date data to power decision making. Eighty-two percent of companies are making decisions based on stale information and 85% state this stale data is leading to incorrect decisions and lost revenue. As companies look to improve customer experiences, adapt to an increased security posture, and embrace how to scale analytics and AI projects, they need to have a sound data strategy and robust approach to data integration patterns.   

Real-time data integration

Increasing data variety, volume and velocity compounds the problem of stale data. Data is constantly changing, and organizations need a way to keep pace with its rapid evolution. Real-time data integration refers to the ability to ingest, process and write data as soon as it is available. This approach contrasts with  batch-style data integration, which processes data on an intermittent or scheduled basis. Real-time data integration offers an answer to these ubiquitous challenges by helping ensure continuous data processing.

Streaming data pipelines continuously consume data in real time from various sources with diverse formats and structures, transform if necessary, and then load to a target system, such as a data lake, data warehouse or any destination of choice. With data continuously integrated as it becomes available, streaming data pipelines provide fresh data for various use cases in a time-sensitive manner.

Use cases that benefit from real-time data integration are those where extracting insights with minimal delay (within seconds) provides business value. Some examples are:

• Real-time reporting and analytics: Processes and analyzes high-velocity data from diverse sources, transforming it into actionable intelligence within seconds, enabling instant insights and data-driven decisions.
• Fraud detection: Provides immediate access to a continuous flow of curated data from across the enterprise, enabling swift response to suspicious activities and empowering businesses to identify and act on potential threats.
• Cybersecurity: Integrates real-time streaming data infrastructure with cybersecurity platforms, breaking down data silos and providing rich contextual information for enhanced situational awareness, while optimizing costs and scalability. 

Introducing IBM® StreamSets, the SaaS for real-time data integration across hybrid and multicloud environments 

According to Gartner, by 2028, large enterprises will triple their unstructured data capacity across their on premises, edge and public cloud locations compared to mid-2023. Just as data formats are changing, data itself also changes over time as a result of many factors, such as changes in user behavior, external conditions or data collection methods. The change in data distribution over time, a concept known as data drift can impact the accuracy of models and systems that rely on consistent data patterns, resulting in unreliable outputs and poor decision-making.

With IBM StreamSets now available, clients can address these issues and operationalize real-time data integration by creating and managing smart streaming data pipelines to deliver the high-quality data that is needed to drive digital transformation. Organizations can: 

• Enable real-time data at scale: Build reliable streaming data pipelines across hybrid cloud environments to decrease data staleness and enable real-time insights and accelerate decision-making processes.
• Reduce data drift with intelligent data pipelines: Insulate data pipelines from changes and unexpected shifts with prebuilt drag-and-drop stages designed to automatically identify and adapt to data drift. 
• Stream any type of data from multiple diverse sources: Create seamlessly adapting streaming pipelines for structured, semi-structured or unstructured data and automatically detect and alert users to changes in schemas.

How to leverage IBM StreamSets

IBM StreamSets offers customers a scalable solution for building reusable streaming data pipelines that adapt to change, enabling fast, reliable decision-making. The product provides a visual-oriented design for building and deploying sophisticated data pipelines without hard-to-maintain custom code. It offers a suite of prebuilt transformations, connectors to a wide variety of sources and destinations and a powerful software development kit (SDK) to drive automation, all of which boost enterprise-scale productivity.

IBM StreamSets leverages a hybrid architecture with a separation between a SaaS control plane and engines. Users can deploy it wherever their data resides, in any geo, cloud, all major hyperscalers, virtual private cloud (VPC) or on premises for secure data processing and reduced data egress. 

Real-time data integration and IBM Data Fabric

Data integration is a key component of a modern data fabric architecture, especially considering the growth of data volume, velocity and variety as data becomes more disparate across organizations’ hybrid, multicloud environments. With data residing across locations and formats, data integration tools have evolved to support multiple patterns of integration styles. 

Given the unique needs of enterprises and due to specific use cases, the IBM approach to a data fabric architecture is composable and consists of highly integrated services. Clients can choose from a set of seamlessly integrated data integration products that fit their needs, whether they be for artificial intelligence, business intelligence and analytics or other industry-specific requirements. 

The  portfolio includes industry-leading tools such as IBM DataStage® for moving and transforming mission-critical data with  extract, transform and load (ETL) and extract, load and transform (ELT) processing. With IBM Databand®, the observability solution for data pipeline monitoring and issue remediation underpinning the entire portfolio, IBM offers clients a seamless and comprehensive solution for designing, deploying and managing data pipelines across all data sources and integration patterns. IBM StreamSets is a strategic addition that enables real-time streaming data pipelines, allowing clients to address a wide set of use cases no matter the style of data integration.

At IBM, we are committed to innovating and evolving to meet our clients’ needs. Now, with IBM StreamSets, users can unlock real-time data to scale insightful decision making, analytics and AI.